Bibliographic record
Abstract
Books reviewed: Manfred F. Boemeke, Roger Chickering, Stig Förster (eds.), Anticipating Total War: The German and American Experiences, 1871–1914 Sidney Fine, Expanding the Frontiers of Civil Rights: Michigan, 1948–1968 Ted Robert Gurr, People Versus States: Minorities at Risk in the New Century Paul Hollander, Political Will and Personal Belief: The Decline and Fall of Soviet Communism Andrew Kohut, John C. Green, Scott Keeter, and Robert C. Toth, The Diminishing Divide: Religion’s Changing Role in American Politics Shawn William Miller, Fruitless Trees: Portuguese Conservation and Brazil’s Colonial Timber Marc Mulholland, Northern Ireland at the Crossroads: Ulster Unionism in the O’Neill Years, 1960–1969. Dickson A. Mungazi, In the Footsteps of the Masters: Desmond M. Tutu and Abel T. Muzorewa Jennie Purnell, Popular Movements and State Formation in Revolutionary Mexico: The Agraristas and Cristeros of Michoacán Ruth Rosen, The World Split Open: How the Modern Women’s Movement Changed America William Shawcross, Deliver Us From Evil: Peacekeepers, Warlords and a World of Endless Conflict George Warecki, Protecting Ontario’s Wilderness: A History of Changing Ideas and Preservation Politics, 1927–1973
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.558 | 0.592 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".